{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*  By: Proskurin Oleksandr\n",
    "*  Email: proskurinolexandr@gmail.com\n",
    "*  Reference: Advances in Financial Machine Learning, Marcos Lopez De Prado, pg 30, https://towardsdatascience.com/financial-machine-learning-part-0-bars-745897d4e4ba"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import Image"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Imbalance bars generation algorithm\n",
    "\n",
    "Let's discuss imbalance bars generation on example of volume imbalance bars. As it is described in Advances in Financial Machine Learning book:\n",
    "\n",
    "First let's define what is the tick rule:\n",
    "\n",
    "For any given $t$, where $p_t$ is the price associated with $t$ and $v_t$ is volume, the tick rule $b_t$ is defined as:\n",
    "\n",
    "$$b_t = \\begin{cases} b_{t-1}, & \\mbox{if } \\Delta p_t\\mbox{=0} \\\\ |\\Delta p_t| / \\Delta p_{t}, & \\mbox{if } \\Delta p_t \\neq\\mbox{0} \\end{cases}$$\n",
    "\n",
    "Tick rule is used as a proxy of trade direction, however, some data providers already provide customers with tick direction, in this case we don't need to calculate tick rule, just use the provided tick direction instead."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Cumulative volume imbalance from $1$ to $T$ is defined as:\n",
    "\n",
    "$$ \\theta_t = \\sum_{t=1}^T b_t*v_t $$ \n",
    "\n",
    "$T$ is the time when the bar is sampled."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next we need to define $E_0[T]$ as expected number of ticks, the book suggests to use EWMA of expected number of ticks from previously generated bars. Let's introduce the first hyperparameter for imbalance bars generation: __num_prev_bars__ which corresponds to window used for EWMA calculation.\n",
    "\n",
    "Here we face the problem of first bar generation, because we don't know expected number of ticks with no bars generated. \n",
    "To solve this we introduce the second hyperparameter: __expected_num_ticks_init__ which corresponds to initial guess for expected number of ticks before the first imbalance bar is generated.\n",
    "\n",
    "Bar is sampled when:\n",
    "$$|\\theta_t| >= E_0[T]*[2v^+ - E_0[v_t]]$$\n",
    "\n",
    "To estimate $2v^+ - E_0[v_t]$ (expected imbalance) we simply calculate EWMA of volume imbalance from previous bars, that is why we need to store volume imbalances in _imbalance array_, the window for estimation is either __expected_num_ticks_init__ before the first bar is sampled, or expected number of ticks($E_0[T]$) * __num_prev_bars__ when the first bar is generated. \n",
    "\n",
    "Note that when we have at least one imbalance bar generated we update $2v^+ - E_0[v_t]$ only when the next bar is sampled not on every trade observed\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Algorithm logic"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we have understood the logic of imbalance bar generation, let's understand how the process looks in details"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```python\n",
    "num_prev_bars = 3\n",
    "expected_num_ticks_init = 100000\n",
    "expected_num_ticks = expected_num_ticks_init\n",
    "cum_theta = 0\n",
    "num_ticks = 0\n",
    "imbalance_array = []\n",
    "imbalance_bars = []\n",
    "bar_length_array = []\n",
    "for row in data.rows:\n",
    "    #track high,low,close, volume info  \n",
    "    num_ticks += 1\n",
    "    tick_rule = get_tick_rule(price, prev_price)\n",
    "    volume_imbalance = tick_rule * row['volume']\n",
    "    imbalance_array.append(volume_imbalance)\n",
    "    cum_theta += volume_imbalance\n",
    "    if len(imbalance_bars) == 0 and len(imbalance_array) >= expected_num_ticks_init:\n",
    "        expected_imbalance = ewma(imbalance_array, window=expected_num_ticks_init)\n",
    "       \n",
    "    if abs(cum_theta) >= expected_num_ticks * abs(expected_imbalance):\n",
    "        bar = form_bar(open, high, low, close, volume)\n",
    "        imbalance_bars.append(bar)\n",
    "        bar_length_array.append(num_ticks)\n",
    "        cum_theta, num_ticks = 0, 0\n",
    "        expected_num_ticks = ewma(bar_lenght_array, window=num_prev_bars)\n",
    "        expected_imbalance = ewma(imbalance_array, window = num_prev_bars * expected_num_ticks)\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that in algorithm pseudo-code we reset $\\theta_t$ when bar is formed, in our case the formula for $\\theta_t$ is:\n",
    "\n",
    "\n",
    "$$\\theta_t = \\sum_{t=t^*}^T b_t*v_t$$\n",
    "<center> $t^*$ is time when previous imbalance bar was formed<center>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's look at dynamics of $|\\theta_t|$ and $E_0[T] * |2v^+ - E_0[v_t]|$ to understand why we decided to reset $\\theta_t$ when bar is formed.\n",
    "The dynamics when theta value is reset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image('images/mlfinlab_implementation.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note that on the first ticks, threshold condition is not stable. Remember, before the first bar is generated, expected imbalance is calculated on every tick with window = expected_num_ticks_init, that is why it changes with every tick. After the first bar was generated both expected number of ticks ($E_0[T]$) and exptected volume imbalance ($2v^+ - E_0[v_t]$) are updated only when the next bar is generated"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When theta is not reset:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image('images/book_implementation.png')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The reason for that is due to the fact that theta is accumulated when several bars are generated theta value is not reset $\\Rightarrow$ condition is met on small number of ticks $\\Rightarrow$ length of the next bar converges to 1 $\\Rightarrow$ bar is sampled on the next consecutive tick."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The logic described above is implemented in __mlfinlab__ package in _ImbalanceBars_"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Statistical properties of imbalance bars. Exercise 2.2 from the book"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from statsmodels.graphics.tsaplots import plot_acf\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    " # imbalance bars generated with num_prev_bars = 3, num_ticks_init = 100000\n",
    "imb_bars = pd.read_csv('../Sample-Data/imbalance_bars_3_100000.csv')\n",
    "dollar_bars = pd.read_csv('../Sample-Data/dollar_bars_ex_2.2.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "dollar_bars['log_ret'] = np.log(dollar_bars['close']).diff().fillna(0) # get log returns\n",
    "imb_bars['log_ret'] = np.log(imb_bars['close']).diff().fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fab536ccda0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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9Pu/+QIUQADApQxVC1s4DAFPliCOOyGtf+9p8+tOfHn7uoosuyhe/+MUkyXXXXZdLLrlkj99/KPw58sgjs2nTpgNyq9iuBEIAwKQMzRAasHYeAJhC733ve3faNvaRj3wkn/nMZ3LWWWfl85//fD784Q/v8Xsfdthhecc73pElS5bkV3/1V3P++edPxZG7Wqmq6fkyt3Tp0mr58uXT8tkAwJ5b8sffzNPbG7n6Zc/NO19w0nQfBwDYQ3fffXdOO+206T4Ge2G0f8NSyg+qqlo60b0qhACASWloGQMA6HoCIQBgUmwZAwDofgIhAGBShraMDQiEAKDrTdcYGfbe3v7bCYQAgI61WlUGC4S0jAFAl+vv78+6deuEQl2oqqqsW7cu/f39e/wePZ1cVEq5LMmHk9ST/F1VVX+xy+vHJ/lcksMGr7m6qqqb9/hUAMCM1BzxhVHLGAB0t0WLFmXlypVZu3btdB+FPdDf359Fixbt8f0TBkKllHqSjyV5cZKVSZaVUm6oququEZf9+yRfqqrqb0oppye5OcniPT4VADAjDc0PSpIdDf+bCADdrLe3NyeccMJ0H4Np0knL2AVJ7q+q6sGqqgaSfDHJK3e5pkpyyODPhyZZNXVHBABmipGBkBlCAADdq5OWsYVJHh3xeGWSC3e55pok/1xKeVeSOUl+cUpOBwDMKA2BEADAfqGTCqEyynO71oi/Iclnq6palOSXkny+lLLbe5dSriilLC+lLNejCADdZ+eWMYEQAEC36iQQWpnkuBGPF2X3lrDfTPKlJKmq6vYk/UmO3PWNqqr6VFVVS6uqWjp//vw9OzEAMG2GVs4nKoQAALpZJ4HQsiQnl1JOKKX0JXl9kht2ueaRJC9KklLKaWkHQkqAAGA/s1OFkEAIAKBrTRgIVVXVSHJVkm8muTvtbWIrSinXllJeMXjZe5O8o5TyoyR/n+TyqqqsHgGA/UyjacsYAMD+oJOh0qmq6ua0V8mPfO59I36+K8nFU3s0AGCmGVkhtF2FEABA1+qkZQwAIMnOW8YMlQYA6F4CIQCgY2YIAQDsHwRCAEDHhraMze6t2zIGANDFBEIAQMeGKoQO6qtrGQMA6GICIQCgY0MzhPp76xlo2jIGANCtBEIAQMeGKoRm99XNEAIA6GICIQCgY43mMy1jA1rGAAC6lkAIAOhYc0TLmAohAIDuJRACADo2cstYo1Wl1TJHCACgGwmEAICODc8Q6q0nidXzAABdSiAEAHSsMWLtfBJtYwAAXUogBAB0bHiG0HAgpGUMAKAbCYQAgI41dm0Zs2kMAKArCYQAgI41B4dKaxkDAOhuAiEAoGON5jNr5xNDpQEAupVACADo2G5bxrSMAQB0JYEQANAxW8YAAPYPAiEAoGPDW8Z6BUIAAN1MIAQAdKyxSyC0XcsYAEBXEggBAB3bfctYNZ3HAQBgDwmEAICODVUIzR4KhFQIAQB0JYEQANCxZnOXLWNmCAEAdCWBEADQsV1nCBkqDQDQnQRCAEDHmq0qtZLM6ml/hRjQMgYA0JUEQgBAxxqtKj21WvqGAiEVQgAAXUkgBAB0rNlqpV4r6au3v0IYKg0A0J0EQgBAx9oVQiW9gxVC1s4DAHQngRAA0LFmq0q9XtJbL0m0jAEAdCuBEADQseEKoZqh0gAA3UwgBAB0rNmsUq+V1GrtKiFr5wEAupNACADo2NCWsSTprdcEQgAAXUogBAB0bGjLWNIOhLSMAQB0J4EQANCxZpX0DAZCfT21DNgyBgDQlQRCAEDHRlYI9WkZAwDoWgIhAKBjjcGh0knSWy9axgAAupRACADoWLNVpaf+TMuYCiEAgO4kEAIAOtZoVanbMgYA0PUEQgBAx5qtaniodG+9lu1axgAAupJACADoWGPkUGktYwAAXUsgBAB0bGSFUHvLmLXzAADdSCAEAHSsPUPIljEAgG4nEAIAOrZThZCWMQCAriUQAgA61mjuvGVsQCAEANCVBEIAQMd2nSGkZQwAoDsJhACAjjVardTrWsYAALqdQAgA6NjICqFeW8YAALqWQAgA6NjOW8a0jAEAdCuBEADQsZ0qhHqKodIAAF1KIAQAdKxdIdT++jCr3p4hVFXaxgAAuo1ACADo2K4zhKqqHRIBANBdBEIAQMcazdYzM4R62l8jbBoDAOg+AiEAoGMjK4T66oOBUEOFEABAt+koECqlXFZKuaeUcn8p5epRXv9QKeWOwV/3llLWT/1RAYDp1mhVqdd3rhDa3mxO55EAANgDPRNdUEqpJ/lYkhcnWZlkWSnlhqqq7hq6pqqq3xtx/buSnPssnBUAmGY7Vwi1f9/RVCEEANBtOqkQuiDJ/VVVPVhV1UCSLyZ55TjXvyHJ30/F4QCAmaOqqp22jPUNzRBqmCEEANBtOgmEFiZ5dMTjlYPP7aaU8pwkJyT51t4fDQCYSYaWiY3cMpYYKg0A0I06CYTKKM+NVRv++iRfqapq1GECpZQrSinLSynL165d2+kZAYAZoNFqBz/1XQKh7SqEAAC6TieB0Mokx414vCjJqjGufX3GaRerqupTVVUtrapq6fz58zs/JQAw7ZqDJULDM4SsnQcA6FqdBELLkpxcSjmhlNKXduhzw64XlVJOTXJ4ktun9ogAwEzQGAyE6ruunTdUGgCg60wYCFVV1UhyVZJvJrk7yZeqqlpRSrm2lPKKEZe+IckXq6ryrRAA9kPN5s6B0FDL2ICWMQCArjPh2vkkqarq5iQ37/Lc+3Z5fM3UHQsAmGkaWsYAAPYbnbSMAQAMzxAaWjvfW28HQwMCIQCAriMQAgA6MrRlrGeXGUJaxgAAuo9ACADoSHPXodJaxgAAupZACADoyPAMofrOQ6UFQgAA3UcgBAB0ZNcKIVvGAAC6l0AIAOhIozn6lrGBwecBAOgeAiEAoCO7bhnr0zIGANC1BEIAQEd23TI2vHZeyxgAQNcRCAEAHdl1hlC9VlKKCiEAgG4kEAIAOjK8ZWwwECqlpK9ey4BACACg6wiEAICO7FohlLTnCGkZAwDoPgIhAKAjQ4FQT/2ZQKi3p6ZlDACgCwmEAICO7LplLGlXCO1oWDsPANBtBEIAQEd2nSGUJL09xQwhAIAuJBACADrSHFw7P3KGUK+h0gAAXUkgBAB0ZLQKoXbLmEAIAKDbCIQAgI6MumWsR4UQAEA3EggBAB1pNIcqhJ75+tBbt2UMAKAbCYQAgI4MVwjVd20Zs2UMAKDbCIQAgI6MvmVMyxgAQDcSCAEAHRlty1hfvWTAUGkAgK4jEAIAOjLqlrEeM4QAALqRQAgA6MhoW8YMlQYA6E4CIQCgI89UCO28ZUzLGABA9xEIAQAdGa1CqK+nloGmLWMAAN1GIAQAdKTRHGWGkJYxAICuJBACADrSbLVSSlLbaYaQLWMAAN1IIAQAdKTRqnaqDkoMlQYA6FYCIQCgI81WtdP8oKQ9Q6jRqtJqmSMEANBNBEIAQEfaFUI7f3XorbcfD6gSAgDoKgIhAKAjo1YIDQZC2sYAALqLQAgA6Eij1dpthlBfz1AgpGUMAKCbCIQAgI6MViE03DJm0xgAQFcRCAEAHWk0R9sy1n6sZQwAoLsIhACAjjRbVer10VvGDJUGAOguAiEAoCOjbRnr0zIGANCVBEIAQEfGmyGkZQwAoLsIhACAjoy/ZUwgBADQTQRCAEBHmq0qtTJ6hdB2LWMAAF1FIAQAdKTRqtKz21DpoS1j1XQcCQCAPSQQAgA6MtoMob56PUmyQ4UQAEBXEQgBAB1pNKvdZgj1DlcICYQAALqJQAgA6Mh4W8YGBEIAAF1FIAQAdKS9ZWznrw59Q4GQljEAgK4iEAIAOjLqDKHhtfOGSgMAdBOBEADQkUZrlBlCwxVCzek4EgAAe0ggBAB0ZPQZQtbOAwB0I4EQANCRRqtKT330ljFDpQEAuotACADoSLtCaOevDr01Q6UBALqRQAgA6Eh7y9jOFUK1WklPrWSHCiEAgK4iEAIAOtJqZbcZQkm7bUwgBADQXQRCAEBHRqsQStqbxrSMAQB0l44CoVLKZaWUe0op95dSrh7jmteWUu4qpawopfyXqT0mADDdRtsylgwGQraMAQB0lZ6JLiil1JN8LMmLk6xMsqyUckNVVXeNuObkJH+Y5OKqqp4qpSx4tg4MAEyPRqsatUJolpYxAICu00mF0AVJ7q+q6sGqqgaSfDHJK3e55h1JPlZV1VNJUlXVmqk9JgAw3ZrN3beMJUlvvWgZAwDoMp0EQguTPDri8crB50Y6JckppZR/LaV8t5Ry2VQdEACYGRqtKj310VvGVAgBAHSXCVvGkuz+zS/ZdVBAT5KTk7wwyaIk/6OUcmZVVet3eqNSrkhyRZIcf/zxkz4sADB9xpohZMsYAED36aRCaGWS40Y8XpRk1SjXfK2qqh1VVT2U5J60A6KdVFX1qaqqllZVtXT+/Pl7emYAYBqMt2Vsu5YxAICu0kkgtCzJyaWUE0opfUlen+SGXa75xySXJkkp5ci0W8genMqDAgDTp9Wq0qoyeoWQljEAgK4zYSBUVVUjyVVJvpnk7iRfqqpqRSnl2lLKKwYv+2aSdaWUu5J8O8kfVFW17tk6NACwbzWrdrf4aBVC7ZYxa+cBALpJJzOEUlXVzUlu3uW59434uUrynsFfAMB+ptlqBz5jbRnbsFWFEABAN+mkZQwAOMA1WmNXCNkyBgDQfQRCAMCEms2hCqHRW8YGBEIAAF1FIAQATKjRagc+PfXRh0oP2DIGANBVBEIAwISemSGkZQwAYH8gEAIAJjTuDKGeYssYAECXEQgBABMab8tYX72eHVrGAAC6ikAIAJjQRBVC27WMAQB0FYEQADCh5uBQ6VG3jA3OEKoqbWMAAN1CIAQATGi8CqG+ei1V9UxbGQAAM59ACACYUKM5zpaxnvbXiQFtYwAAXUMgBABMaKj6p6c++tr5JNnRUCEEANAtBEIAwIQa420ZUyEEANB1BEIAwISa484Qaj8nEAIA6B4CIQBgQo1xtow90zImEAIA6BYCIQBgQuNWCA22jO1QIQQA0DUEQgDAhJ6ZITR2hdB2FUIAAF1DIAQATKjZHKoQGmWodF2FEABAtxEIAQATGq9C6JmWMWvnAQC6hUAIAJhQs4OWsQEtYwAAXUMgBABMaPwtY+3ntIwBAHQPgRAAMKFOtowNCIQAALqGQAgAmNC4M4S0jAEAdB2BEAAwoeEKofrYM4S0jAEAdA+BEAAwofEqhHp7BEIAAN1GIAQATKg5GPb01Hb/6qBlDACg+wiEAIAJdTRDqFnt0zMBALDnBEIAwITG2zLW22PtPABAtxEIAQATsmUMAGD/IhACACY0XoVQvVZSigohAIBuIhACACbUHKdCqJSS3notAwIhAICuIRACACbUbFWDlUC7B0JJMqtey46GodIAAN1CIAQATKgxGAiNpbenloFmcx+eCACAvSEQAgAm1Gy1Rp0fNKS3XlQIAQB0EYEQADChiSqE+npqhkoDAHQRgRAAMKFmq5qgQqiW7QIhAICuIRACACbUrhAa+2tDX72WHQ2BEABAtxAIAQATajbHrxDSMgYA0F0EQgDAhCbcMlavZUAgBADQNQRCAMCEmq1Weuq2jAEA7C8EQgDAhCbeMlZXIQQA0EUEQgDAhCbaMtZXLxkwVBoAoGsIhACACU20Zay3bqg0AEA3EQgBABOaqEJIIAQA0F0EQgDAhCaeIVTTMgYA0EUEQgDAhJqt1oQVQgNNW8YAALqFQAgAmFCjOUGFUL1oGQMA6CICIQBgQs1WlZ66ljEAgP2FQAgAmJAtYwAA+xeBEAAwoU62jDVaVVotc4QAALqBQAgAmFAnW8aSZECVEABAVxAIAQATmmjLWF+9/ZVC2xgAQHcQCAEAE5qoQqh3cOD0DqvnAQC6QkeBUCnlslLKPaWU+0spV4/y+uWllLWllDsGf7196o8KAEyXiWYI9fXUk6gQAgDoFj0TXVBKqSf5WJIXJ1mZZFkp5Yaqqu7a5dLrq6q66lk4IwAwzRrNibaMtcMiq+cBALpDJxVCFyS5v6qqB6uqGkjyxSSvfHaPBQDMJBNXCBkqDQDQTToJhBYmeXTE45WDz+3qVaWUH5dSvlJKOW6UqWuVAAAgAElEQVRKTgcAzAiNVpV63VBpAID9RSeB0Gjf/nadGHljksVVVZ2V5JYknxv1jUq5opSyvJSyfO3atZM7KQAwbSbaMtY7GAhpGQMA6A6dBEIrk4ys+FmUZNXIC6qqWldV1fbBh3+b5OdGe6Oqqj5VVdXSqqqWzp8/f0/OCwBMgwm3jPWoEAIA6CadBELLkpxcSjmhlNKX5PVJbhh5QSnlmBEPX5Hk7qk7IgAw3SacITRcIWTtPABAN5hwy1hVVY1SylVJvpmknuQ/VVW1opRybZLlVVXdkOR3SymvSNJI8mSSy5/FMwMA+1ijVaU27lDpwS1jKoQAALrChIFQklRVdXOSm3d57n0jfv7DJH84tUcDAGaKiSqEhmYI7TBDCACgK3TSMgYAHMCqqkqzVaVeG/trQ68tYwAAXUUgBACMq9lqzwUad4bQ4FBpLWMAAN1BIAQAjKsxGAiNt2Wsz9p5AICuIhACAMbVSYXQMy1jtowBAHQDgRAAMK6OKoSGWsYazX1yJgAA9o5ACAAYV2cVQu3XVAgBAHQHgRAAMK5Gqz0XqF6feMuYodIAAN1BIAQAjKujLWOGSgMAdBWBEAAwrmYHM4RqtZKeWskOFUIAAF1BIAQAjKuTCqGk3TYmEAIA6A4CIQBgXJ1sGUvam8a0jAEAdAeBEAAwrmcqhMb/2tBbr2XAljEAgK4gEAIAxtVodlghVDdDCACgWwiEAIBxdTpDSMsYAED3EAgBAONqtNohT71uqDQAwP5CIAQAjMuWMQCA/Y9ACAAY16S2jBkqDQDQFQRCAMC4Ot0y1levZaDR3BdHAgBgLwmEAIBxdVoh1NtTskOFEABAVxAIAQDjag4OlTZDCABg/yEQAgDG1Wh2OEOobu08AEC3EAgBAOManiE00dr5nloGVAgBAHQFgRAAMK5Gh2vn+7SMAQB0DYEQADCu5vBQ6U62jAmEAAC6gUAIABhXpxVCtowBAHQPgRAAMK6hLWMTrp2v17JDhRAAQFcQCAEA4+p4hlBPLdvNEAIA6AoCIQBgXM/MEOpsqHRVaRsDAJjpBEIAwLgazaEKofG/NvTWa6mqZwIkAABmLoEQADCu4Qqh+sQtY0kyoG0MAGDGEwgBAOPqeMtYvf21YkdDhRAAwEwnEAIAxtXplrG+wQoiFUIAADOfQAgAGNdQhVC9aBkDANhfCIQAgHE1W1VqJal13DImEAIAmOkEQgDAuBqtasINY8mIQEiFEADAjCcQAgDG1WxVE84PSp5pGduuQggAYMYTCAEA42o0qwk3jCVJnwohAICuIRACAMbVbLVSr08cCD3TMmbtPADATCcQAgDG1Z4h1EkgNLh2XssYAMCMJxACAMbV3jLW+QwhLWMAADOfQAgAGFfnFULtrxUDAiEAgBlPIAQAjKvZqjqaIaRCCACgewiEAIBxtSuEJv7KMLRlzAwhAICZTyAEAIyr2Wql3knLmAohAICuIRACAMbVaE5yy5i18wAAM55ACAAYV7NVdVQhNKteT6JlDACgGwiEAIBxdbxlrKd9jZYxAICZTyAEAIyrVXVWITS0dn6HCiEAgBlPIAQAjKs9Q2jirww9tZJSkgEVQgAAM55ACAAYV6czhEop6a3XBEIAAF1AIAQAjKvRaqWnPnEglCR99Vp2NGwZAwCY6QRCAMC4Oq0QSpK+nloGms1n+UQAAOytjgKhUsplpZR7Sin3l1KuHue6V5dSqlLK0qk7IgAwnTrdMpYkvfWiQggAoAtMGAiVUupJPpbkZUlOT/KGUsrpo1w3N8nvJvneVB8SAJg+k6kQ6q3XrJ0HAOgCnVQIXZDk/qqqHqyqaiDJF5O8cpTr/jTJ+5Nsm8LzAQDTrF0h1FmXeV9PLdsFQgAAM14n3+4WJnl0xOOVg88NK6Wcm+S4qqq+Pt4blVKuKKUsL6UsX7t27aQPCwDse2NVCG3atClJcsstt+Sf/umfkgwNlRYIAQDMdJ0EQqPViA8PByil1JJ8KMl7J3qjqqo+VVXV0qqqls6fP7/zUwIA06bRau02Q+jRRx/NggUL8sUvfjHvfe978yd/8idJtIwBAHSLTgKhlUmOG/F4UZJVIx7PTXJmkltLKQ8n+fkkNxgsDQD7h2Zz9wqhz372s9m6dWsuuOCC/OZv/ma++93vZtmyZemtlwwIhAAAZrxOAqFlSU4upZxQSulL8vokNwy9WFXVhqqqjqyqanFVVYuTfDfJK6qqWv6snBgA2KcarSo99Z0DoS984Qu59NJLc+KJJ+byyy/PwQcfnI9+9KPp66nZMgYA0AUmDISqqmokuSrJN5PcneRLVVWtKKVcW0p5xbN9QABgeu06Q+iee+7Jvffem1e96lVJkkMOOSSXX355rr/++jQ2PZWlW76TfPyi5MmHpuvIAABMoKOVIVVV3VxV1SlVVZ1UVdWfDT73vqqqbhjl2heqDgKA/ceuW8ZuvPHGJMnLX/7y4eeuvPLKzJ8/P/0/W5b/e+OfJ2tWJLd/bJ+fFQCAznS2QxYAOGDtWiH0yle+Mp/85Cdz/PHHDz932mmn5dFHH82rFm9sP3Hipckd1yXbN+3r4wIA0AGBEAAwrl23jJ188sm54oordruulJIzNn0/d1WLkwt/K9mxJXl8xT48KQAAnRIIAQDjGlkh9Oijj+YrX/lKnn766d2ue+CuO/KC//Cv+dR9RyYLTms/ueaufXlUAAA6JBACAMbVniHUDoRuuummvOY1r8natWt3u+6o1uo8vqnK7at7kkOPT3rnJGt/sq+PCwBABwRCAMCYWq0qVZXUB4dKf+9738v8+fNzwgkn7HbtwRvuzUlH1PLg4xuTWi1Z8FwVQgAAM5RACAAYU6NVJUl66u0KoZ/85Cc588wzU0rZ/eLH7shpxxyUjasfbT9ecFqy5u59dVQAACZBIAQAjKk5GAgNzRC67777csopp4x+8ao7svi4hRl4clU2b96czDs52bw22bZxXx0XAIAO9Uz3AQCAmavRaiVJemol69aty7p160YPhLZtTJ58IGec+/LMfeK52bRpc+YcsrD92tOPJf2H7MNTAwAwEYEQADCmkRVChx9+eO6///7MnTt39wtX35kkOfa8F+eI1pE5bN68ZOsx7dc2rkrmn7qvjgwAQAcEQgDAmIZnCNVKarVaTjrppNEvfOxHSZINh52eqrEy657akGMPObb92sZV++KoAABMghlCAMCYnqkQquXGG2/MRz/60dEvfOxHycFHZ0f/vDzy16/LX/z5f0jmDlYIPS0QAgCYaQRCAMCYRlYIfelLX8oHP/jB0S9c/ePkmLPT11tPz9x5efSRR5Le2cnsI5KNj+3DEwMA0AmBEAAwpmbzmRlCK1euzKJFi3a/aGBLsvYn7UCoXkv9kPlZuXJl+7VDjtUyBgAwAwmEAIAxDW8Zq48TCK25K6la7UCop5aeuUdm1c9GBEJaxgAAZhyBEAAwpqEZQrWSsQOhx+5o/37MWekdrBB6/LFVaTab7TlCWsYAAGYcW8YAgDENzRDatmlDtm3bNkYg9ONk9uHJoceld9WaHHTS+Xn7i5Zkx44dqc+Zn2xZl7RaSc3/QwEAzBQCIQBgTEMVQocdPi9bt25Na7CFbCerfpgcfVZSSvp6apm18LS88e2/kP7+/mTOkUnVTLatTw46Yh+fHgCAsfivOgBgTCO3jPX39+eggw7a+YLN65LVdyaLL0mS9NZLqlYzD97/QJ588snkoHnt67as25fHBgBgAgIhAGBMzcGKoP91+3fy7ne/O5s3b975goduTVIlJ/27JElfvZbmpnV57S9ekK9+9avPBEKbn9h3hwYAYEICIQBgTI3BtfMr/tf385GPfCSzZs3a+YL7/1vSf1hy7LlJkr6eWuoHHZ4keeyxx9otY0myRSAEADCTCIQAgDENzRB68ok1mT9/fnp6Rowf3PJksuK/Jqf+UlKrJ0l667WUnt7MPfTwdiCkZQwAYEYSCAEAYxqaIbR+3docddRRz7xQVcmtf5Hs2JJc9K7hp3vr7a8Whx+5IKtXr04OGqwQ0jIGADCj2DIGAIxpqEJo3RNrcszRRyc/uTm55Y+Tp1cn2zcmP/e25KjTh6+f1dMOhA494sh2hVBvf9J3sAohAIAZRiAEAIxpqEKosWNHjjl0VnL9m5MFpyXnvDE5eklyzpt2un6oQuhlb7wizz95sF3soHkqhAAAZhiBEAAwpqEtY//wzf+R0753dXL37ORtNyf9h456fW+9JElOO/95+eWLT2g/edA8FUIAADOMGUIAwJiGKoT6mptSVnw1OfNVY4ZBSXvLWJI89eSTufXWW7Nt27b2pjFbxgAAZhSBEAAwpmarSmPjmrz78lfn+z/d1A6ExjHUMvaj730nl156aR566KFk9uHJ1qf2xXEBAOiQQAgAGFOzVaWxYU1u+tbt2bA9ycKfG/f6vsFAaM5h7e1iq1evTvoPS7ZteLaPCgDAJAiEAIAxNVpVmpvXJ0mOOu6kZNbB415fq5X01EpmH9oOhB577LF2i9m2jcngPCIAAKafQAgAGFOzVaW5ud3udfSpSzu6p7deS/8hRyQZrBCafViSKtmuSggAYKYQCAEAY2q0qszZvCq1ksw79Rc6uqe3XlLvPzj9/f2DFUKHtV/QNgYAMGNYOw8AjKnZbOXw+pYcsaCW+oJTOrqnr6eegWaVf/iHf8hJJ52UVPe3X9i6Pjn8WTwsAAAdEwgBAGNqtKq84vln5v970bLkiJM6uqevXrKj2cov/dIvtZ94eG37923rn6VTAgAwWVrGAIAxNVtVFpfVqXpmJ3OP6eie3p5adjRb+fGPf5wbbrjhmZaxrQIhAICZQiAEAIyp0arymS/fkg//qD+pdfa1obdey0CjlU9+8pO5/PLLB4dKxwwhAIAZRCAEAIyp0Wxl2QNPZtX2OR3f01dvVwgtXLgwTz31VLa0+tovaBkDAJgxBEIAwJg2bVyfHc0qRx2zsON7entqGWhWOe6445IkP1u7Pil1LWMAADOIQAgAGNP2x+9Lkhyz6PiO7+mrlww0mlm0aFGSZOXPftZuG1MhBAAwYwiEAIAxDax5IEly1KITO76nr6eWHc3qmUBo5cr2YGkzhAAAZgyBEAAwpoN2rM/SY2tZ9H+c0fE9vYMzhJ7znOfk9ttvz8tf/vJ2hZCWMQCAGaNnug8AAMxc5y+em/e94+DkvIs7vmdoy1hfX19+/ud/vv1k/6FaxgAAZhCBEAAwprnbH8+29KX/oHkd39PXU8tAs5Uk+frXv56tW7fmNf2HJesfebaOCQDAJGkZAwDG9Hf/8K287LotSSkd3zO0dj5JPvGJT+TP//zPtYwBAMwwAiEAYEw/feyJrN7ceRiUtAOhrQPNVFV7sHR7qPRgy1hVPUsnBQBgMgRCAMCYntq4JQcfPGdS95y56NA8sWkg963ZlEWLFmXt2rXZVuYkrUYysPlZOikAAJMhEAIARldVeeLpHZkzd+6kbnvpGUellOTmOx8bXj2/atNgZZDV8wAAM4JACAAYVWvr+qzZ3Er/3MMmdd+Cuf05f/ER+cadq4cDoZXrd7RftGkMAGBGEAgBAKPavu5n+eVTejJv4QmTvveXzjw69zz+dI4++eysXLkyF//Che0XDJYGAJgRBEIAwKhmtzbmv77uoCw+95JJ33vZmcckSW59YH0WLlyY+sGDa+u1jAEAzAg9030AAGCG2rQmSfJ0z+GTvvXoQ/vzc885PDffuTqNH9+UY+bW87pEyxgAwAyhQggAGNVXbvinHP2Bp/OzJ7ft0f0vO/Po3PXYxnziU3+b62/45/aTWsYAAGYEgRAAMKrHVq3M45urNOces0f3X3bm0UmS+twjs/Kx1e0nVQgBAMwIHQVCpZTLSin3lFLuL6VcPcrr7yyl3FlKuaOUclsp5fSpPyoAsC89vmZNaiWZNfeIPbp/0eEH5exFh2ZT/ZCsXPmzZNahZggBAMwQEwZCpZR6ko8leVmS05O8YZTA579UVbWkqqpzkrw/yV9N+UkBgH1qzdonc8ScnvT27PnIwZctOSYbaodk9erVGeidq2UMAGCG6KRC6IIk91dV9WBVVQNJvpjklSMvqKpq44iHc5JUU3dEAGA6rHlqQw6fMyv1Wtnj93jZmUenPvfIlFota3YcpEIIAGCG6OS//BYmeXTE45VJLtz1olLK7yR5T5K+JP9utDcqpVyR5IokOf744yd7VgBgH3r+c3py+LxFqe1FIPSceXNywYtfmVm//KosmvP/J9s3TnwTAADPuk4qhEb7FrhbBVBVVR+rquqkJP9Pkn8/2htVVfWpqqqWVlW1dP78+ZM7KQCwT73n/OTlL7pgryqEkuRXzj0+d6x8Ott6DlYhBAAwQ3QSCK1MctyIx4uSrBrn+i8m+dW9ORQAMM22b0pj++Y8mcPSU9+7QOgXT52Xdd/8WD79r6sFQgAAM0QngdCyJCeXUk4opfQleX2SG0ZeUEo5ecTDX05y39QdEQDY17as/Wl6//Tp/ONtd6de62gp6ZhOOeawbL371vzLirUCIQCAGWLCGUJVVTVKKVcl+WaSepL/VFXVilLKtUmWV1V1Q5KrSim/mGRHkqeS/PqzeWgA4Nm19pH2/+00+g/PXhYIpZSSeQuOycNPbEm1/emUVivZy5AJAIC909Ee2aqqbk5y8y7PvW/Ez//XFJ8LAJhGa1Y+mCRpzDlqryuEkuTkE5+Tn95/V0qq9mDp2Yft9XsCALDn/PccALCbx1c+nCTZNufo9OzlUOkkOeXExXl605b2A21jAADTTiAEAOxmzer2/ohNsxemvrc9Y0kWL16c/r6+tKoqTz31xF6/HwAAe0cgBADs5rQFPXn3xXPTmjNvSiqE3ve+9+V7N38+tVLyg588vPcHBABgrwiEAIDd/MJxPfnQ65+bqtaX+hQEQkly/LFHJ0nufPCRKXk/AAD2nEAIANjNutU/y9a+eWm0qimpEFq1alVe/rb35pYHG1m1enWe2jwwBacEAGBPCYQAgN28/uPL8+8+8IM0q2pKtoz19/fnpn/+dv5tTTNzqi35l7sen4JTAgCwpwRCAMBu1mzclgXzDk1ziiqEDj/88MyePTsrN1Y57qCB3HTnY1NwSgAA9pRACADY2Y6tWbOpmfnzjkizVU3JDKFSSo499tj8bHM9pxzSyl2PbZyCgwIAsKcEQgDATlobV2ft5irzFyxIkimpEEqSo446Kmu3lszN5mzZ3piS9wQAYM8IhACAnTz5swfTrJL5Ry9MktTrUxMInXXWWTn6sIMyJ1uyZUczrVY1Je8LAMDkCYQAgJ30DjyVv3zxrFx08SVJpq5C6G/+5m/yhd86Lwc1N6Wqkm2N5pS8LwAAkycQAgB2cmjZnN+/aFZO/7mLkmRKtowN6z80/a1NSZLN2wVCAADTRSAEAOxk3aqHcv+TrWzrPSzJ1FUIfe1rX8s5//6/ZeP69UmSLQPmCAEATBeBEACwk7+/+bac/NFNWbuhXckzFVvGkmT79u350cNPZv2GDUlUCAEATCeBEACwkzVr16ZWkkMPOyLJ1FUILRjcWvbk+k1JKhVCAADTSCAEAOxkzbqncuTcvlSDXxOmqkLoqKOOSpKs3dzMQdmeTVbPAwBMG4EQALCTNU8+nQWHHpTm4Fr4nilaOz9UIfT4plYOyeZsGdAyBgAwXQRCAMBOHt+wJQuOOCSNwUBoqraMHX744XnB0jMyf04tc8vWbFYhBAAwbXqm+wAAwAyyY1v+6KJ66ue8+JkKoSlqGavVarn17z+cfOH/zD9sVyEEADCdBEIAwDM2r80vn9KbvOh5WdFqJZm6GUJJkv72KvtDypZsNlQaAGDaaBkDAIbtWL8q33m4kbUDs6a8QihJ3vGH78/Lrtucw2pbssXaeQCAaSMQAgCGrXrw7rzwc1vytdtWjJghNHWB0NYdzdzzRCvzerapEAIAmEYCIQBg2JqVDyVJjlp0wogKoan7unDUMQuzZnP1v9m77/C4qjv/4++r6TOaGXVpZLl3G4xtTAsGEiCJCWlsGgHSSAJZwpINm80mu/vbTdn0bEgjCWwgJIFQ0uk1dLCNsY17b5JVrTZNmnp/f8xoLFnFsuMZgefzeh49M7r3njnXM5Z05zPfcw6Vlj5VCImIiIhMIAVCIiIiktPWfACA2qmzSaZOfIVQTV09kQS4kkFVCImIiIhMIAVCIiIiktPW0gJA7aQphyuELCcwEKqpydyJ9miVMREREZEJpEBIREREctrb24FMcJPMwypj8+fP5/Kl5fhK+onEVCEkIiIiMlG07LyIiIjkfHCxl3mVS3C5XKTSQeDErjJ29tlnc/ZnlrCp01SFkIiIiMgEUiAkIiIiOTPdYWaefypAXlYZA8Dpx2M2aQ4hERERkQmkIWMiIiKS8+T6Rta0ZIKgfKwyFo/H8V/7IP/39H6tMiYiIiIygRQIiYiISEain8890Mk3/7gOyE+FkN1uJw30hvtUISQiIiIygRQIiYiISEaknbawSW1NNQCp7KTSJ3IOIYCaslK6wnGi8RSmaZ7QxxYRERGR8VEgJCIiIgAke1ro7DOpravPfJ/KzxxC1eVeOiNJrOkYsWT6hD62iIiIiIyPAiEREREBoKNxFwA19Q3AoDmELCe4QqiynI6oiZc+LT0vIiIiMkEUCImIiAgAbY27AahtmA7kb5Wx91x4Du+bb8NnRLT0vIiIiMgE0bLzIiIiAsCcCnj5k25mv/3dQH5WGQP45BWXAb9jTSyqiaVFREREJogCIREREQHAnejk7LkBqA0A+asQMh0+InGTUjNEREvPi4iIiEwIDRkTERERAFav28wdm0pIpTIhTb5WGbvroefwfiuE2dNCVBVCIiIiIhNCgZCIiIgA8Pvnt/KZu3dTkh0ilq8Koaq6SQCU9HWqQkhERERkgigQEhEREQDau4PUlnkwjEwAlEoNzCF0gpedr5+auRPtUYWQiIiIyARRICQiIiKQjNPW00dtpf/wpjxVCFUHJgOQivYQ0SpjIiIiIhNCgZCIiIhAuJW2iEltdWVuUyptUmKQqxg6UapragBIRMNEY6oQEhEREZkIWmVMREREINRKW9hkaW1dblMybZ7wJecBXC4X//m2Why1HlUIiYiIiEwQBUIiIiICwWZWf9qD8ZF/zW1KpdMnfLjYgK//w1yebTZ4XhVCIiIiIhNCgZCIiIhAqIUGXwnMWZzblKkQyk8g1Jt2Ewu1qEJIREREZIJoDiERERGhed8OvvFCkj2tPblt6bSJxZKfQOiqX27k83dv1ypjIiIiIhNEgZCIiIiwbdsO/vOpKPsPHMhty2eFUHW5l+5IgkhMFUIiIiIiE0GBkIiIiNDW2gxAbW1tblsqbeZtDqGaynIORVJEYom8PL6IiIiIjE2BkIiIiNDWfggYGgjla5UxgOrKChJpCPd25eXxRURERGRsCoRERESKnWnS1tmN1VJCeXl5bnM+K4Sqq6oAiHU25eXxRURERGRsCoRERESKXSxIezBOTbmXkkEVQfmcQ+ic0xfx00ucuKxmXh5fRERERMamZedFRESKXaiVW97lpPetNw3ZnEqn81YhNHvuPGafaed5FAiJiIiITAQFQiIiIsUu2Iy1xKBy8uwhm5Op/A0ZS9u9bGlPkbQ25uXxRURERGRs4xoyZhjGCsMwthuGscswjC+NsP9GwzC2GIaxwTCMpwzDmHriT1VERETyItTCvz/Vz1+e3zRkcyptYrXkKRBy+Fn08wj7175APJnOSx8iIiIiMrqjBkKGYViAm4FLgAXAhw3DWHDEYeuAZaZpLgL+AHz3RJ+oiIiI5IcZbOZ/X47z8ms7hmxPpk0seVplzOqrocZjkIx0E40n89KHiIiIiIxuPFd5ZwK7TNPcY5pmHLgHeM/gA0zTfNo0zWj225VAw4k9TREREcmX3pZ9xFNQWz/0z3cqj5NK4yon4DXoD/cSiafy04eIiIiIjGo8gdAkYPAA/6bsttF8EnhkpB2GYVxjGMYawzDWdHR0jP8sRUREJG/aDu4HoLa2dsj2ZB4nlcbqoM5rJRoOE42pQkhERESk0MYTCI10JTjikiCGYVwFLAO+N9J+0zRvNU1zmWmay6qrq8d/liIiIpI3bS0HgeGBUF4rhIBav4tgOKoKIREREZEJMJ5VxpqAyYO+bwCajzzIMIyLgf8ALjBNM3ZiTk9ERETyrbezHUuJMUKFkInTlr9A6BPnTWbGDFQhJCIiIjIBxhMIvQLMNgxjOnAQuBy4YvABhmEsAW4BVpim2X7Cz1JERETyI53iXVOjxB/9b1i4cMiufFcInT6vAU/pIbpVISQiIiJScEcdMmaaZhK4HngM2ArcZ5rmZsMwvmYYxruzh30PKAV+bxjGesMw7s/bGYuIiMiJE+kAM0VJ2SRKjlhRLJnK3ypjAD3pUjbsaqW1TZ8liYiIiBTaeCqEME3zYeDhI7b916D7F5/g8xIREZFCCDZz8+o4+xof4XtnfGrIrnxXCO3ugU/e3cQXlq2Bt5yat35EREREZLj8fewnIiIir3+hFh7fk+TxlzcO25VMp7FY8hcI1U/KLHPf3tqStz5EREREZGQKhERERIpZqIW2sElNXWDYrnxXCE2enFmzoqulMW99iIiIiMjIFAiJiIgUs2ALbRGT2kDDsF3JtIklj4GQ019Lpcugp6Mpb32IiIiIyMgUCImIiBSzUAvtEZPaurphu/JdIYSrnIDXIHioNX99iIiIiMiIxjWptIiIiJyc+jubqPLac8O3BstUCOXxsyN3Bb98l5OHp74rf32IiIiIyIgUCImIiBQxZ387+29+H1z+z8P2FaJC6KwGKxsrnfnrQ0RERERGpCFjIiIixSzUDN7hE0oDJFPpvM4hhKucbYdSvPjcs6TT6fz1IyIiIiLDKBASEREpVvEoz2zr5JKvPcj+/UCSQpsAACAASURBVPuH7S5EhdDju5Pcce/DdHZ25q8fERERERlGgZCIiEixCrey7VCaR1dvx2azDdudTJtYLHkMhCw2Kr0uAFpaWvLXj4iIiIgMo0BIRESkWIVaaQubAFRXVw/bnfcKIaDM7wUUCImIiIgUmgIhERGRYhVqpS2SprKibFiFkGma+V9lDCgrLwOgubk5r/2IiIiIyFAKhERERIpVqJW2iEltbe2wXelM4VDeK4TKK6oAVQiJiIiIFJqWnRcRESlWoRZqSq2Uzj9r2K5kdtWvvK4yBlhLK3jw01M569rP5LUfERERERlKgZCIiEixCrfx8ytmwT//etiuVLZEKN8VQklHOW8KJLB4vHntR0RERESG0pAxERGRYhVqAW9gxF3JbCCU7wqhtKuMF3b08H+3/l9e+xERERGRoRQIiYiIFKne9iZO/eor/OEPfxi2L5UqTIWQ6azg3s0Jfvj9b+W1HxEREREZSoGQiIhIkWpubmVTYw/xeHzYvlyFkCXPlwqeagKlBu1t7Zimmd++RERERCRHgZCIiEgxikdo7QoCEAgMHzZWqDmESrzV1HsN4vE4PT09ee1LRERERA5TICQiIlKMQq20hDOhT11d3bDdBVtlzFtLwJu5HNHS8yIiIiKFo0BIRESkGIVaaQ1nQp+xKoQsRn4DIbu/hkBppo/m5ua89iUiIiIih2nZeRERkWIUbqXGY3DReWfj9/uH7R6YQ8hqyW8g5PBVc+YkK8///J8496KL8tqXiIiIiBymCiEREZFiFGrlqkV2nnzsYYwRqoBSBVp23uN0ErV6qbRERzwPEREREckPBUIiIiLFKNQCFgc4y0bcnSzQsvMuu4VO08cv73+Je++9N699iYiIiMhhCoRERESKUaiN5b+K8E833DDi7rQ5UCGU30sFu7WELvz8aeVe/vznP+e1LxERERE5TIGQiIhIMQq1sLU9QTq7mtiRkgVadh6gt8RPoLREq4yJiIiIFJACIRERkSIU62qmK5IYccl5gFSBlp0HCFoqmFSaViAkIiIiUkAKhERERIpQW1smfBlpyXko3BxCAGFrGQ0eBUIiIiIihaRASEREpNjEwrR0BgHGqBAqzCpjAFFbBQGvQSKRIBKJ5L0/EREREVEgJCIiUnzCbZTaDa645Fxmz5494iG5OYQs+Q+EYo4KbjzHTt/ul/F4PHnvT0RERETAOtEnICIiIgUWamFhjYW7/uXrMHPuiIccrhDK/2dHcUdlZmhatDPvfYmIiIhIhiqEREREik2oNVMB5B15/iAo7CpjSWcFHZE0H/+Xr/PMM8/kvT8RERERUSAkIiJSfEKtXPtAP3OXv2vUQwq5yljSXYPNYvDrB55j7dq1ee9PRERERBQIiYiIFJ9QC01hA39Z+aiHFLJCyOYsxWG34bRbtdKYiIiISIEoEBIRESk24TYOhg0mTZo06iGFXGXM7bDRaZQRKHfR3Nyc9/5ERERERIGQiIhI8Qm10tSboqGhYdRDkqmBCqH8Xyp4HBY6TR91XpsqhEREREQKRIGQiIhIkQkfaqK3Lzm+CqECLDvvtlvpNH3MqLBgt9vz3p+IiIiIaNl5ERGRopMKtvNvHziL5cuXj3pMIecQ8jgsHDL93PH+cqz/+mje+xMRERERBUIiIiLFJRbCXxLh2zdcDmMEQoVcZcxtt7KdcizRDkglwaLLExEREZF805AxERGRYhJqIxgzCRr+MQ8raIWQ3UqbWcEL+2JcfNFbaGxszHufIiIiIsVOgZCIiEgxCbfy09Vx/MuvJhqNjnpYYVcZs9BqlhNNwFPPvsCBAwfy3qeIiIhIsVMgJCIiUkxCrRwMpvF6fbjd7lEPO1whVIBVxuxWWs1KAt5M+KSl50VERETyT4GQiIhIMQm10BQySTjLSGdDn5EUtELInqkQCpRm+tLS8yIiIiL5p0BIRESkmIRaaQwC3mo6I/FRD0umCrnKmJUuvJS5bVgtJQqERERERApAgZCIiEgxCbXSGDSxeqto6e0b9bBUOo1hQEmBKoRMSuhz1XLuvFp8Pl/e+xQREREpdlrXVUREpJiEWvnkBZP5lfc8mnv6WdQw8mHJtFmQ6iAAh7UES4lB0FbFM1+YCR//ckH6FRERESlmqhASEREpIulQC8uXzsE1bTGtY1YImQWZPwjAMAzcdgs9lmoIakJpERERkUJQICQiIlJEutubWdtegplK0NLbP+pxmQqhwl0mlDqsdFkqufmJXSxduhTTHH3CaxERERH5+ykQEhERKRaxEI9vDfLftz5KouvgmIFQISuEIDOPUEdJJbF4nHXr1tHT01OwvkVERESKkQIhERGRYhFqZW9PGoDApCljTiqdTKcLNocQZFYaazcrmFaWuTTZt29fwfoWERERKUYKhERERIpFqJW93Wkc7lKWzQ7Q3PP6qhBqNssVCImIiIgUiAIhERGRYpGtEHKV1zCjupS2YD/p9Mhz9SRThVtlDMBjt3IwVc5Uf6bP/fv3F6xvERERkWI0rkDIMIwVhmFsNwxjl2EYXxph//mGYaw1DCNpGMb7T/xpioiIyN8t1MLenjSe6snU+50k0yaHwrERD02lTSyWAlYIOaw0JfxUuAwuOWsuNTU1BetbREREpBgdNRAyDMMC3AxcAiwAPmwYxoIjDjsAfBz43Yk+QRERETlBQq387yVeTllxJXV+FwDNo0wsXehVxjx2C70JA8NTzcP//jauuOKKgvUtIiIiUozGc6V3JrDLNM09pmnGgXuA9ww+wDTNfaZpbgDSeThHERERORFCLSydHWDR6WcS8DsBaB1lYunCzyFkJRpLgX8SBA9q2XkRERGRPBtPIDQJaBz0fVN2m4iIiLyBNO3fwx93QLk9TX1ZtkJolImlC7/KmIVIPIlZNpWv/e5lJk3SpYaIiIhIPo0nEBrpavC4PrYzDOMawzDWGIaxpqOj43geQkRERI7To2t2c+Pd23EmwpS7bTisJaMuPT8RFUJpE1L+qbhSvbS0tNDT01Ow/kVERESKzXgCoSZg8qDvG4Dm4+nMNM1bTdNcZprmsurq6uN5CBERETkepsn+1i4Mw2DhnOkYhkHA76RlzDmEClshBNBfOplpvsznTlppTERERCR/xhMIvQLMNgxjumEYduBy4P78npaIiIicUH3d7OtO4vN6aKj0AVA3RiA0ERVCAFHPZKaVZS5P9u3bV7D+RURERIrNUQMh0zSTwPXAY8BW4D7TNDcbhvE1wzDeDWAYxhmGYTQBHwBuMQxjcz5PWkRERI5RsJm93Wk8ZRXUZSeUrve7aB2tQihV+FXGAIKuSUwrywRRqhASERERyR/reA4yTfNh4OEjtv3XoPuvkBlKJiIiIq9HoVb29qSxT6+j3G0DIFDmpDXYP2I1UMErhByZS5KgvZaZHgtXr1jKnDlzCta/iIiISLEp3Ed/IiIiMnFCzTx0hZu5F30Qw8gEPXV+F6m0SUcoNuzwZDpd0EBooEIonLRg+Cdz26eWsmLFioL1LyIiIlJsFAiJiIgUg2ALi+sslM8+I7epPjt0bKSVxiZsDqF4EsqnYnbtpbu7u2D9i4iIiBQbBUIiIiJFYNOmjfzwVQt+x+E//QG/C2DEiaUnapWxSCwF5dP44p2vMnnyZEzTLNg5iIiIiBQTBUIiIiJF4KEXN/D5B7upLrXltgWyFULNPa+3CqFpTPX0E4lEaGtrK9g5iIiIiBQTBUIiIiJFYNv+Nso8NqbV1+S2lbltOG0lI640lkqbWC2FC4RKs5NKR+KZCqGZ5Zm+d+/eXbBzEBERESkmCoRERESKwI7mIHWVvlxVEIBhGAT8rhGHjGUqhAp3meC0lWAYEI0loXw6syoyfe/atatg5yAiIiJSTBQIiYiInOxSCXZ0xCirqKTW5xyyK+B3jjipdKHnEDIMA4/dmqsQmlpWQkmJoQohERERkTxRICQiInKS627cxqGoiasyQJ3/yEBorAqhwgVCAG67JTOHkLsCu6ecb330XC688MKCnoOIiIhIsbBO9AmIiIhIfpVb+un8opfrk+dS43UM2RfwO2kL9pNMpbFaDn9OlEynC1ohBOBxWDOrjBkGVM/ji7UWePObC3oOIiIiIsVCFUIiIiInu1AzFS4Dyqdjswz90x8oc5I2oSMcG7J9QiuEAKrnEm7awrp16wp6DiIiIiLFQoGQiIjISe6eP/yVbz4fw/DVD9tX73cB0NwzdNhYoecQAjJzCMVSmW+q5/GL51tZunQp3d3dBT0PERERkWKgQEhEROQkd++jL/DbDUnc/uph+wbmFDpyYulUqrCrjAG4HUMrhGaWZ/rXxNIiIiIiJ54CIRERkZPctv1tTK5yU5etBhpsoEKotXeECiHLBFQIxQ9XCA0sPX9kIPTcjg5++/K+gp6biIiIyMlGgZCIiMhJLJFIsLstRGVF2bAVxgB8Lituu2XYkLEJm0Molq0Q8tUzo9YHwK5du4Ycd+tze/jWI9tIp82Cnp+IiIjIyUSBkIiIyElsx44dJFImZdW11PmGB0KGYVDnd9IaHDpkbKJWGQsPBEKGgWfSfCaVO9mxY0fuGNM02dISJBpPsb8rWtDzExERETmZKBASERE5iTXu2Y7bBvbqqSNWCEFm2NjgCqF02iRtMkGrjKUwzWzlT/U8fvrucq6//vrcMW3BGF2ROABbmoMFPT8RERGRk4kCIRERkZPYijPnEfqyl2TV3FEDoTq/c8ik0qlsIDMRFULJtEk8lc5sqJ7De6dFOGPhzNwxW1p6R7wvIiIiIsdGgZCIiMjJrLeREsOgmeoRh4wB1PudtIdiJLJBTCo7N0/BVxmzWwCIDlp6vqvP5C933ppben5rSwiAhnJX7r6IiIiIHDsFQiIiIiexy675EretjdPjqMPjsI54TKDMhWlCeygGZFYYgwmoELJnzi8ysPR8zQJea01x2bVfZs2aNUBmmNjUSjdnTKvQkDERERGRv4MCIRERkZNUb28vf3l2Pa3REmze2lGPGxhK1tKTGTaWSg1UCBV4DiFHtkJoYOl5fwPzp1QBsG3bNgC2tARZEPCxIOCjNdhPZzhW0HMUEREROVkoEBIRETlJbdy4EYDJgQpqy9yjHlfvdwHQ0puZWDqZzgwds1omqEJo0EpjtXNOp8xlYevWrYRjSfZ1RjKBUH1mSXoNGxMRERE5PgqERERETlIbNmwAoKw6MOr8QQCBsmyFUHZi6cNzCBV+UmkYVCEEGPVLmF8JW7dsZntrENOEBfU+5gcygZAmlhYRERE5PgqERERETlIbN26kzFVC1F036gpjAF6HFY/dklt6fqLmEBqYVDpXIQRQv5h5VSVs27o5N2fQgnofFR47Ab9T8wiJiIiIHCcFQiIiIiepCr+Pd8wq4aBZPWYgZBgGgTIXrdkhYxO1ythIFUIEFvPv5zl45qefY0tLkDK3LVfttCDgY0uLAiERERGR46FASERE5CT1jX+9hrv+wc1Bs2rMIWMAAb8zN2Rs4lYZy1YIxQdVCPkbmNVQw1xbK1taQiwI+DCMzHktqPexuyNCfyI10sOJiIiIyBgUCImIiJyETNOEzt0A7DPrqB1XIDRQIZSZVLrwq4xlK4RigwIewyBes4if3v0Ia1e+yILs3EEA8wM+UmmTnW3hgp6niIiIyMlAgZCIiMhJ6J577mHK+ZezryfNXrOOwBhDxgACfhcd4RjxZHrCKoRcthEqhABbwxL+3/37CG18Mre6GJALhzSxtIiIiMixUyAkIiJyElq7di1tnUEqyvxELH4qPPYxjw/4nZgmtAX7SaYmZpUxS4mBy2YZOocQYDQsY1l9CUbrliGB0JQKNx67RRNLi4iIiBwHBUIiIiInobVr17JocildzgZqfM7cvDujCZS5AGgN9ucmlbZaChsIAXgclqGrjAFMOZsz6i0EO5qZ5LXmNpeUGMzXxNIiIiIix0WBkIiIyEnGNE3WrVvH0lqDA0b9UYeLAdRnj2nu6csNGSv0KmMAbrt1WIUQ7gqmT64jnTbZvHHDkF0L6n1sbQmRzp6ziIiIiIyPAiEREZGTzP79++nu7mZpZT87k7VHnVAayC1L39I7qEKowEPGANz2ESqEgJJJiygxGB4IBXyEY0kau6OFOkURERGRk4ICIRERkTeYNfu6+PFTO8c85rqPfYDlUyys768dV4WQ12nD67DS2ttPcoJWGQPwOKzDJpVuD/Wz1raYzi96+eSKJUP2DcwppHmERERERI6NAiEREZE3mJue3MEPntjBno6Rl1ufNm0aN9/wLhbWWNiYbBhXhRBAoMxJc0/f66BCaOiQsS3NQV5ML8TvLIHdfxuyb06tlxIDtmoeIREREZFjokBIRETkDeRQOMbLuzsBeHhjy4jH7N69m1TLJtJWFwfM2txwsKOp87toDfYPmkNoAiqE7FaiR1QIbWkJ0oOX/Y55vP367/HYY4/l9jltFmZWl2piaREREZFjpEBIRETkDeTRTa2kzcwy8Q9uGB4IpVIplixZwud/eB9h32zSlIxryBhkJpZu7uknlRqoEJqASaUdI1cITa5wUb/0El7Z3cVdv759yP4F9T4NGRMRERE5RgqERERE3kAe2tDCzGoPnz5vBttaQ+xqHzps7LXXXiMUCnF2VYQO9yyAcQ8Zq/M7ORSOEU1kApnXU4XQgoAP+6LLuGyelb/e/wD9/f25/QsCPpp7++mOxAt9uiIiIiJvWAqERERE3iDaQ/2s2tvJpYvqecepAQxj+LCxF154AYDz6vrYZ5+FYUCNd7wVQi4gs/Q8gNUyAXMIOSxEBi07H40n2XsowvyAD+pO5YNnNRCM9PH444/njhmYWHq88wjFk2n6jlzaXkRERKTIKBASERF5gxgYLvbORQHq/E7OmFrBQ0cMG3vqqaeYVl/NZH8Jm0rmUelxYLeO7899oCwTHDV2ZZZwn6gKoXgyTSKVWelse2sI08xUAWEYXPjeq6h0Gdx75x25NvMD2ZXGxhkI3Xjfet790xdyk2eLiIiIFCMFQiIiIm8QD25oYXZNKXNqvQBcuijA9rYQO9tCAESjUZ544gneuXQS2Dy8Fq+nzu8Y9+MPzDXU2J2tEJqgVcYAotkKnoGQZ6AKyHbGx/jXN9k5p/5wmFNV6qDW5xjXPEIHOqM8tLGFne1hnt7WfqJPX0REROQNQ4GQiIjIG0BbsJ9X9nXxzkX1uW2XnFqHYZCbXNput/PXv/6Vf1xaAg2n0xxMUOdzjbuPQHbIWFP3xFUIlTqsALl5hLY0B/E5rUwqy/47Kmfyb1ddzPVTdkDy8JxBCwK+cVUI/eqlvVgMg2qvg9te2Hvi/wEiIiIibxAKhERERArs7tUHeN/PX6I/Mf55bB7Z2IJpwqWL6nLbarxOzppewUMbWzBNE6vVylvPWcwCYzdMXU5rsP+YKoQ8Dis+p5WmXIXQRKwylgmEBlYa29ISZEG9D8MYFE6d+zkihxr5223/nds0P+BjV3uYWHL05zTUn+D3a5p456IAn1o+nZf3dGp1MhERESlaCoREREQKqCca55sPb+XV/d38+qV942730MYW5tV5mVXjHbL90kX17GoP89KmPdx44400vXA3YBKb+TZ6ognqxrnC2ICA30U8mZm/ZwLyIDy5IWNJUmmTbS0hFgT8Qw+adTHfWFfG2677Nu0H9wOZIWXJtMnOtvCRD5lz7yuNhGNJPrl8BpefMQW33cLtL6pKSERERIqTAiEREZEC+vmzuwnHkiys9/GzZ3bT25c4apvW3n5e2dfNpacGhu1bsbCOEgO+9r0fctNNNxHZ8gR462lxzgagzj/+IWNweGJpmKAKIfvhCqF9nRH6Eqnc/EE5hsEVn/saqTTc863PAtlJpxl9YulU2uSOl/ZxxrRyTm3w43fbeP/pDdy/vpmOUCx//yARERGR1ykFQiIiIgXS0tvHHS/u47LFk/je+0+jty/BLc/uPmq7h7JLy79j0fBAqNrr4PSAk7/94Q7ec+nbmRt+CRa8h9ZsyHHsFUKHj5+QVcYchyuEBoZzzQ94hx13yoqPs3h6Jb/506NwYCVTKz247ZZRh4A9saWNpu4+rj53em7bx980jXgqzV2r9h/zeZqmVigTERGRNzYFQiIiIgXy46d2kjZNPv/WOSyo9/GexfXc/uJe2oP9Y7Z7aEMz8wM+ZlaXjrg/teEBkn1hPvuWBkin4MxP09qbecw6/7EPGRswMauMZSuE4im2tgSxWQxm1wwPhACuvv7feLUlxSs3XYkl1sO8Ou+oFUK3v7CXhnIXb1t4eA6mGdWlXDSvhjtX7h/3fE6maXLD3ev44C0vjzlfkYiIiMjrnQIhERGRY/Tophb+6e51RGLJcbfZ3RHmvjVNXHnWVCZXuAG48a1zSKZMfvy3naO2O9jTx9oDPbxzhOoggIMHD/Lo726lZv4ZvDlyP8x/J1TOpDV4vIHQ66RCKJZkS0uQWTVe7NaRL1c+9qlrKfW4eXBdM9z3MU6tc7G1JTisemdjUy+r93Xx8TdNG/Zvunr5dA6F4zzwWvO4zu83L+/n/teaeWVfN999dPtx/AtFREREXh8UCImIiByD1xp7uOGe9TzwWjP/+ofXxj106AeP78BhLeH6C2fltk2t9HDFWVO4Z3Uj+w5FRmz3SHa42EjzBwGUlJTwwXdezAMrDtGftmJe8l0gM+9QqcOaW8Z9vF5PFUJbmoO5uYFG4vP52LJ1G1/94e2w91k+fuh/CffHc6ukDfjVi3vx2C188IzJwx7jTTMrmVfn5fYX9x31tdzWGuQbD2/lzXOr+eg5U7nthb08s739mP+NpmmSTmvImYiIiEwsBUIiIiLj1B7q59rfvkp1qYPPvmUmD29s5eandx213YamHh7a2MKnzptBVenQZeCvv3AWNksJ//vEjhHbPrihhVMm+ZhW5Rm6I9wOz/+AwINXcseCZ1lUZfKR2L+xOZQ5rrW3/5irg2DopNITUSHkzq4ydqAzQnsoNnxC6SNMnjwZFn+YtsWfY3rzg3zd+iu2NPfk9rcH+3lgQzMfWDYZn9M2rL1hGFx97nS2tgR5eU/nqP30J1LccPc6fE4b3//Aafz7O+Yzt9bLF37/2jFNSh2OJfnQrSu59CcvcCisyaxFRERk4igQEhGRonPfmkY+9es1tPT2Hf3grFgyxT/euZaevji3fvR0vvC2ubx3cT3/+8QOntzSNmbb7z22nXK3jU+fN33Yvhqvk08un84DrzWz6WDvkH2NXVHWN/Zw6an1g04kBA/9C73fWsCH/vHf2NEWhYu/Qv+1q9lozM5NQN0a7D/mCaXh8JAxS4mBYRQ+ELJZSrBbS1izvxtgzAqhAU8//TRTL/8ujzrezVXWp6h//suQygzn++3K/STTJp84d9qo7d+9uJ4Kj53bX9g36jH/89AWdrSF+cEHT6Oq1IHTZuHHH15CqD/JF37/2rgqfiKxJJ/41Wpe3d/N3kNhrvrlKroi8aO2ExEREckHBUIiIvKGY5omof6jL9d+pHTa5NuPbOOLf9jAk1vbeO/NLw4LYUbr7yv3b+bV/d187/2nsbDej2EYfPt9izil3s8/37ueXe2hEdu+uOsQz+88xGffMgvvCBUqANdcMIMyt43vPTZ0TpqHjxwu1roRbrmA+Mrb+ODDHv60Hdrf/H1Y/nnKKqs5d1YVD21owTTN464Qctut+F22CakOGuCxW9ianRx6PIHQ2WefzdSpU/nEj5/kx32XcGrbX+DOf6C/t4O7Vh3g4vm1TK30jNreabNw1VlTeGpb24hD9x7f3MqdKw/w6fOmc/6c6tz2uXVe/vPS+Ty7o4PbX9w75jlG40k+cccrrD3Qw48vX8JtHzuDvYciXPnLVfRExx8KxZNpbnpiB999dNu4J8IWERERGYkCIREReUPZ0xHmQ7euZOnXn+CHT+4gnkyPq11/IsX1d6/lF8/u5sqzpvDQDcuxlpTwwVte5qmtY1f43LnqAHevbuS6N8/kXacdrtZx2izc8pHTcdpK+PRvXqW3b2hIZZom33l0G/V+J1edPXXUx/c5bVz35pk8u6ODl3cfHrb00MYWFjX4mVLhgjW/gv+7iEg4xPtfPoXH1x/glltuYfny5bnj33lqgANdUV5r6qUjHDuuCiHIVAlNxPxBA9x2K2kTJpW58LtHDtEGc7lc/OlPfyIcDvOVu1bzpb6Pw4GXSf/sTazof4RPnVl91Me46pypWEsM7nhp35Dtrb39fPGPG1hY7+MLb587vN3ZU3nrglq+8+i2UcPFvniKT96xhjX7urjpQ4u5dFGAc2dV8X8fXcbujjBX3baK3ujRA879nRE+8IuX+NFTO/nZM7u57GcvjRpEjmVXe5hd7eFjbiciIiInFwVCIiJyzBKp9DENtxps08FePnnHK5z+9Sf4/mPbx10dkUyl+cWzu7nkR8+ztSXI8llV/PDJnbzrJy+wvrFnzLaHwjEuv3Ulj2xq5T8vnc//vPcUFtb7+fN1b2JmdSmf/s0a7hilwmPVnk6+ev9m3jK3mn952/BAoL7Mxc+vOp2m7iifu2cdqUFDhx7d1MqGpl4+/9Y5OG2WMc/xo+dMI+B38t3HtmGaJgc6o2xo6uUDc21w30fhwX+m2b+U8+5z8eDfXuLmm2/m6quvHvIYb19Yh81i8OuX9pFKm9QeR4XQwL9pQiuEsiuNzR9HddCAhQsX8uCDDxLpbOX7P7uTfZf8jsakj2/abuPMP54Nv343PPrvsP530LEd0kODxBqvk3edVs99axpzwV4qbfL5e9cTS6T58YeX4LAOfw0Nw+A771tEhcfODfesIxofuvJcfyLFp3+zhpV7O/nBBxfz7kGB4vlzqrnlI6ezozXMR25fNSxQHOxPa5t4x4+eZ19nlF9ctZTbP76MtmA/7/zJC9y9+sC4Jjc/2NPHjfeu5603Pctbb3qWG+9dz8GeY/s5YPNajwAAGzBJREFUTqdNnt/ZwUu7Do17QnURERF5fRpXIGQYxgrDMLYbhrHLMIwvjbDfYRjGvdn9qwzDmHaiT1RERA5LpNI0dkWP6w1Zb1+CP77axDce2sKzOzpIpMZXYQPQ3NPHDx7fzvLv/I1zvvU33nPzi9y3ppG++NGHrmxtCXLtb9fwzp+8wJr93Zza4OenT+/ivO88zQ+f3EFwjCFgm5t7ee/PXuTbj2zjzXOreerGC/jVJ87kto8to7cvwT/87EX+58EtI57HrvYQ7735Rba1Bvn5lafzqfNm5ObGqfE5uffas7lofi1feWALX7l/85BA52BPH9fdtZYplW5+9OElo4YkZ0yr4CvvXsgz2ztyw76SqTTfe3w7s2tK+YelDUd9fpw2C/988WzWHejh8c2tPL96NZ+x3M+Vaz6Iuf1RuPgreD92L+5SHw8++CDXXXfdsMfwu20sn1WVW0I9cJwVQtOrPPhdR6/MyZeBlcaONqH0kS644AJ+fu/DlC55B3/onMLbI1/ljwt/hnHahyEWhDW3w1/+EW4+E74/Cx74ZziwErI/R1efO51oPMV9rzQCcMtzu3l5TydfffdCZlaXjtpvhcfOTR9czN5DEb72wJbc9v5Eimt++yov7j7E995/Gu9dMmlY27fMreHnVy1la0uQj96+etjPQag/wefvXc+N973Gwno/j3zuPFacEuDCebU8+rnzWDa1gi//aSOf/d3aUauMgv0Jvv3INt7y/Wd4cGML154/k2vPn8mDG1t4y/ef4duPbBvz5w8y8x/9+qV9XPSDZ/nIbau54pereNtNz3HXqv3j+vkfeD4e2tDCP975KjfcvY4nt7SNu8JvQCKVZtWeTtY39milNhERkb+TcbQ3E4ZhWIAdwFuBJuAV4MOmaW4ZdMx1wCLTND9jGMblwGWmaX5orMddtmyZuWbNmr/3/EVkApmmedyTzsaTaTrCMapLHditx1asmE6bNPf2cbC7j4YKN/V+5zGdR2c4xtaWEE3dUaZWelgQ8I1rWApk5gHZdDDIhqYe9ndGmV1bymkNZcwLeEesHhgskUqz8WAvq/Z0sWpvJ3s6IpwyycdZ0ys5a0YFc2q8lIxRldHYFeXZHR08t6ODl3Z3Eo4lqfE6OH9ONefPqea8WVWUe+wjtu3tS/DkljYe3tjCczs7SKRMSgxIm1DmtvG2BbVcuqieN82sxGYZ+nqk0ibP7ejgrlX7+du2dkzgzXOqOX1qOX9Z38yu9jBep5X3LW3gyrOmMLvWO6T9zrYQP3xqJw9taMHrsPKp82bwieXT8DltbGsNctMTO3hscxt+l41rzp/Bx940LbdUen8ixU/+tpNfPLuHcredr79nIZccsfx6sD/Bdx7Zxl2rDjClws2333cqb5pZBcBLuw5x7Z2v4rBauO1jyzhtctmIz08qbfKth7fyyxf2cvH8Gn50+RJKDIP3/+IlDnRG+cv1544ZCAz4jz9v5K5VB/jxh5fQF0/yb3/cyC0fOZ23L6wbfnC4A/Y+C7ufho6tEGrFjEeI9sewk8BqJth2KM3dByfx5x2w+tX1uFyuo/7c/eHVJr7w+9cAePCflnPKJP9Rz/tIof4E3ZEEUyrdx9z2RLjylyt5cVcnv7jqdFacMsJzN4aOUIwzvvEkNouBPXiQbT/7DMuWLWPFihWcc9aZnDmriorobtj1JGx/BBJRqFkAy66GRR/iQ7/eTFN3Hz/+8GI+dMtK3r6wjp9esWRcv2O+8+g2fv7Mbn525VIuml/DZ377Kk9v7+C771s04pL3gz2+uZXr7lrLogY/v/nkWZQ6rKxv7OGGu9dlqs8umsP1F84aFkqm0ya3Pr+H7z+2nRqvgx99eAlnTKsAMr9n71y5n5/8bSc9fQkuWzyJf3n7XCaVuYBM4Pm/j23nT+sOUu62ccNFs7nyrKlDfic3dkX59Uv7uHdNI6H+JIsnl/GJc6eRTJnc/uJeNjcHKXPbuPyMKXz0nKnUZx97QCptsnJPJ39Zd5BHN7USyv7eSqTSdEcTlLttXLoowGVLJrF0SvmIz3NPNM4z2zt4cmsbz+7oINSfqcKqKnVw4bxqLppfy3mzq3JB4kgau6K8vKeTlXs6Wb23C5fNwtkzKrNfFVQesfrfkRKpNNtaQqw90M1rjT247BaWTCln6ZQypld5xvX/o7cvwZbmIFtagnjsFhbW+5lTV3rUvx0DTNOkubefnW0hPA4rc2q9xxzcDnyYUOqwUu11HNff8L54Cru1ZEKrCEVEZGyGYbxqmuayox43jkDoHOArpmm+Pfv9lwFM0/zWoGMeyx7zsmEYVqAVqDbHePCTJRD60ZM7sVkNylx2ytw2ylw2/G4bZW47ZS4bbruFVNqkty9BT1+Cnmic7sjh+z3RBA5rSaat2065O/s4bhvlbnuufa5tNEFXJJ67P9C+3G2j3JNpP/AY5R47HruFZNqkO9tvVySe+YrG6Y7E6Y7GcdksVGTbVnjslHvsVGZvPXYLiZRJTzTTpiucvc0+Tk80gdNmyR0/cFvhtlNRerh9VyTOoXAs127gfnc0gdtuobI007bC4xh0306pw0osmc616Qxnbg+F43SGY3RF45Q6rFRm21WVOqgqtVOZvR1o3xGK5dodCsdy33dF4rmLokzbTLtqr4MqrwOvw0pfIkV7MEZHOEZ7MEZ7qJ/2UOZ+VySG12mjxuugxuegxuvM3a/2OvE5rUTiKVp7+2kP9tOa/Wrrzdx2huP4XTZq/U7qfJmvGp+Duuz3fpeNUCxJS08/zb19tPT009LbR3NPP63BPjpCMcrcdur9TgJlLur9Tur8LgJ+J/VlLsrdNrqjCQ5299HUHeVgTx9N2ftN3Zn2laV2JpW5aCh301DuYlL54fuVHjuHwnEOdEVp7IpyYNBXY1eUtmA/1V4HUyrcTKnwZG4rXUypcDO5wk2Vx0FbqJ+9HRH2HIqw91CEPR1h9h6K0NjdRyqdCSUmV7iZUeVhelUp06s9zKjyMKPaQ43XycHuPna2h9jZHmZnW5id7SF2tYeJDvpE2mO3MKvWy+yaUubUljK7xsvs2lLqfE72dUbZ2pK5AN+a/WoLDl/qeVKZi/kBL/MDPhYEfMwP+Kgvc7GjLcSGpl5ea+zhtaYedrSFGPhQ2mO3EMmeh91SwvyAl9Mml7GooYzFk/00lLvZ0NTLqj2drNrbxav7u+nLTgI7q6aUWdWlbDzYmxuyUea2cca0Cs6aXsFZ0yuZXu3hlb1duRBoT3ay20llLi6YW83cWi+v7Ovi+Z2H6O1LYBiwqKGMC+ZUc8GcKmZUlfK3be1DQqB6v5N3nBrgHYsCLAj4eG5HBw9vbOHJre2EY8kh4dDsmlL+vO4gv1t1gIM9fVSVOvjQGQ1cfsYUJldkggLTNFm9t4u7Vh3g0U2txFNpzpxewZVnTWF+wMfPnt7FX19rxm2zcPXy6Xxq+YwRw7dNB3u56YkdPLWtnQqPnWvPn8Epk/z8v79uYk9HhPef3sB/XjqfMvfIgRfAyj2dfOmPG9jXGeXDZ05mQb2fr96/mRnVHm7/+Bk0lB893Pjty/v47/s3Mz/go6HcxeNb2rjtY8u4cF7tUdtC5g34lb9cycaDvZQ6bEwuc/CnTy/GSPRB8CB07sZsXE1y7wukWzaRNiFs+DhUOpe6SVMpr6zkkdcO8vV7VrGtsZPu7l4Mw2DFihXccsstmSXWj6K3L8Gy/3mCRMrklf+4mGrv2G90X48+/Zs1PLGljee/+Jbc/7VjccY3nqQjFONTp1dgbnuShx56iNWrV+cq6p588kkuuugiGndto+XFu6lpehjLoW1g89BetYzfd8+iyTaNoCPAb667mDJ/GZQc/U17IpXm/T9/ib2HIpw2uYzndx7im5edyhVnTRnXeT+6qYXP/m4dS6eU8ea5Ndz0xA5qfU5+dPlilmVDntG81tjDDfeso7Eryj9dOJs5tV6++9g29ndGOXdWJV++ZP6o4eCmg71865GtvLirk2mVbr64Yh4VHju/enEvT2xpo8QwuOTUAJ84dxpLp5Tn2pmmySv7urn9hb08vqU183/1lDquPncaDquFv6w7yAMbmmkLxih1WFlxSh2XLZnE2TMqSWWHnv1lfTNPbGmlP5FmcoWL9y6exHsWT8Iw4KmtbTy5tZ1X93eTSptUldq5cF4NF86rpT+RGhIQ2a0lvGlmJRfNr+WieTWkTZOVe7p4eXcmBBr4PVvhsXPW9Aqi8RSv7OvK/S2ZU1vK2TMqOWdGJWdOryCZNll3oJu1B3pYd6CbDU29xLLVTNVeB/3xFKFYJpgqc9tYPLmMJZPLWTq1jNMmlxFLpNnc3Mvm5iCbm3vZdDDIga7osOfeWmIwp9bLKZN8LKz3c8qkzN+fWCLNttYQO9pCudsdraFcnwMCfidzar3MrfMyN3s7q6aUWCLNro4wuzvC7OmIsDt7/0BnlGT2j5jXYWVGTSkzqz3MrD58O7XSQ38yxYHOKPs6I+zvjLL3UIT9nRH2dUbpCMWwWQwmV7iZVulhauXQ20nlLmLJTPDU2BWlsbuPxq4oTd1RGrv6ONjTh8dhYXJ55lphcrmLhgo3k7PXHgG/k1gyMyz5YE8/zT192a/M/dZgPx6HhXq/i/oyF5PKMrf1ZZlrn+pSB7FkmtZg5pqpLdhPS28/rdmvtlCMUoeFOl+mr1q/k4DPmbn28jupcNuJp9K0BTPXe23BftqCMdqz33eEYngcFmp9Tmp9Tqq9jux9B7VeJ2VuW+7ac+D4juy1Z0coc+03cO05+KvG66C61InPlbl2HXy9O3C/IxSjOxrH47BSVeqgOnfNm7l+Hbh2Hbh27gzHORTJXD93ZW8Htx+43q4cdP3ssVuIpw6378q+Xxi439uXwO2wHL5uzz7GwJc7237gfUd3ND7ktrcvgddhzbxfOOL9R4XbjstuIZZM0RM93L5n0PufYH8Sj91KhSfz3qnCY8+9b6rw2HHaDrcfeP/T25d5z9EdjRPqT1LqsObaDNwO3B9o3xsdeL92+D1bT1+ccH8Sj8NKudueec/nGngPl3kP6LCO0r4vQW80QSiWxOuwDmk7+D3kke17Bz1Gb1+CcGzg/O3Z9jb8A+8/XXbs1pIx20diKUqd1iFtM7d2/C4bdmsJ/YkUwb6R20fjqdzzl+s7+z7Y77Jhs2Ta9x7RtqcvQTDbv9dpHdb3SO0H9zvw/EXjh9sPPu+x2g+0HTh/nyvb3mXHl21b5sq0t1pOnhl1TmQg9H5ghWman8p+/xHgLNM0rx90zKbsMU3Z73dnjzk02uOeLIHQqV95LPdJ1UhsFoNEavTneOAT+uNt//fu99gtxJLp3MXBsbb3Oq30J1KjHjNWe2uJQZnbRjSeGvLm/shjRju3gSArEk/SM0qZ/Fjt/S4bFR47of4kXZHYiK/DaO2tJQbVXkeufXuon/7E8LL30dp7nVbqfE4qS+309iVpC/aPuPTwSO1LDKjNXrhUlTrojSZozl7wHPlcW0qMIcNfAEodVhrKXTSUu6j2OukMx3JB0ZHzV4z0/7PW58gFPrU+Jx2hWC4gag32M/hXypHtnbYSpleVMiMb+tT5nbT29mfCoo5MYNQ3aNUcw2DI49X6HMyuyVzszqn1Ul/mpKm7j13tYXa0ZUKjjlBsxPbWEoNZNaUsCPhYUJ+54J5c7mZvZ4QtzYfDoj2HIsOeM8hc8J/WUMZpDf5c6FNVaqe5t58NjT2sb+phQ2MvGw/2Eo4N/50wr86bCXqybzaqBn0a3dgVZdXeLlbt6WT1vi72dw590+C0lXD2jErOn13NBXOrmXHEp9GptMmGpp5ccLS+sWfI8z44BFoyuWzET4T7Eyme33mIhzY058KhAefOquTKs6Zy8fzaMau5OsMx/vBqE79bfSD3b3DZLHz0TVO59vyZVIxSvTTY+sYefvDEDp7b0QFkwq9v/cOpQ1Z2Gkt/IsVNT+7g/57bQ9qE82ZXcfOVS/GNsrrXSJ7e1s71v1tLJJ7iX98+l8++Zda42wK8smErZy9bitWMg5kmbWZ+Dn5yiZPrzrCzvsPKkp91DWt35513cuWVV7Jy5UouuHgFlro5/L9/vJKPfOh9NDQcfcjZYJ+84xWe33mIbV9fMWbV2evVjfeu54ktbWz4ytuOq4LhY7ev5uXdnbz05QtzP2vBYJA1a9awatUqrrnmGiorK/nOd77Dl740bCQ8rf9SSm1pCf/9dD/ffCGOz2HQ+cML4Jqnj9r3/s4I7/jR80TiKb7+3lP4yBiTiY/koQ0t3JCdi+rSUwN887JTx13BGI4l+a+/bOJP6w4CMLfWy5feMY83z6k+6vNomibP7Ojg2w9vY3tbZqLqMreNK86cwkfOmUrA7xqzfWNXlN+u3M/dqw/krotsFoML5tRw2ZJJXDS/ZtR5tMKxJI9tauUv6w/y4q5DQ35/zavzcvH8Wi6aX8NpDWXD/j8nUmle2dfFU1vbeWprG/uO+P1Z7rYNqgSqZHZNae4xEqk0mw72ZiuHulgzKCAaYLeUcMokH0umlLNkShlLppRT73dimrC7I8zaA92sO9DDugM97GgPMdJl9dRKN6fU+1lQ7+OUSX4WBHy5atPNzb1sag6y+WAvnSNcB0DmemVw4DO7ppRoPMX2thDbWzNfu9rDxLPDf4/822mzGEyrzIY+NZkPXyKx5JCwqKW3P3f8ke0h8/d3aqWHaZVuplS4CcdSuYBof2dkyPM20rWDx25hcoU794FTOJbMhkR9tPT2DTl+pPYD1z71ZS7qfE4i8WQuJDryb+5I1z4APqeVgN9Fjc9BOJakLRsOHXnsaO3t1hJqsh8gRuNJ2oKxEef9Gu3azzDIfIDpsROOJekIx0YcMjnWtetAkBKJJemKxkf8/zZWe3v2Q+RILDXitQqMfe1eYoDPZSMaS+X+vx1Le8hch0biyRHPfTztHdaSXDh7PO3Hen7G0/5o7JaSUZ8btc9/+7/39fM6rDx+4/lH/Zv3RnAiA6EPAG8/IhA60zTNfxp0zObsMYMDoTNN0+w84rGuAa7JfjsX6ARGDY3kpFSFXvNio9e8+Og1Lz56zYuTXvfio9e8+Og1Lz56zU8OU03TPOonqqMPtj6sCRhco94ANI9yTFN2yJgfGPbxp2matwK3DnxvGMaa8aRWcvLQa1589JoXH73mxUeveXHS61589JoXH73mxUeveXEZzyC5V4DZhmFMNwzDDlwO3H/EMfcDH8vefz/wt7HmDxIRERERERERkYlz1Aoh0zSThmFcDzwGWIDbTdPcbBjG14A1pmneD9wG/NYwjF1kKoMuz+dJi4iIiIiIiIjI8RvPkDFM03wYePiIbf816H4/8IHj6P/Wox8iJxm95sVHr3nx0WtefPSaFye97sVHr3nx0WtefPSaF5GjTiotIiIiIiIiIiInl/HMISQiIiIiIiIiIieRCQuEDMP4gmEYpmEYVdnvDcMwfmwYxi7DMDYYhrF0os5NTjzDML6efV3XG4bxuGH8//buLNSqKo7j+PeXmUYRNmdeQR8ksjKLEKEXabQBrSgopKSEEAoMgsp8iKCgCCpoeqnIwDJpILGizAyf1MiUciorysq6L40EhfXrYa+LhzilxTl3c/f+feBw91p7H/jDjzOtu/ZaOrH0J/eGkvSApB0l11ckjes4t7hkvlPShXXWGb0j6SpJWyX9Kemsv51L5g0laXbJdZekO+quJ3pP0tOSBiV91NF3lKTVkj4pf4+ss8boLUkTJa2VtL28ry8q/cm9oSSNlbRR0paS+d2lf7KkDSXzF8omQ9EgkkZJ+kDSqtJO5i1Sy4CQpInA+cCXHd0XAVPK40bgiRpKi/55wPY029OBVcDQGlTJvblWA6fangZ8DCwGkDSVauH5U4DZwOOSRtVWZfTSR8AVwLrOzmTeXCXHx6jey6cC15S8o1meoXrtdroDWGN7CrCmtKM59gK32j4ZmAncVF7byb25fgPOsX06MB2YLWkmcD/wUMn8e2BBjTVGfywCtne0k3mL1DVD6CHgNqBzAaO5wLOurAfGSRpfS3XRc7Z/6mgexr7sk3tD2X7L9t7SXA8MlOO5wHLbv9n+HNgFzKijxugt29tt7+xyKpk31wxgl+3PbP8OLKfKOxrE9jqqXWQ7zQWWluOlwGXDWlT0le09tjeV45+pfixOILk3Vvku/ktpji4PA+cAL5b+ZN4wkgaAS4AnS1sk81YZ9gEhSXOAr21v+dupCcDujvZXpS8aQtK9knYD89g3Qyi5t8MNwBvlOJm3TzJvrmTbXsfb3gPV4AFwXM31RJ9ImgScAWwguTdauXVoMzBINdP7U+CHjn/w5T2+eR6mmqjxZ2kfTTJvlQPadv6/kvQ2cEKXU0uAO4ELuj2tS1+2QBtB/i1326/aXgIskbQYuBm4i+Q+ou0v83LNEqqp58uGntbl+mQ+QhxI5t2e1qUvmTdDso1oMEmHAy8Bt9j+qZo8EE1l+w9geln38RXg5G6XDW9V0S+SLgUGbb8vadZQd5dLk3mD9WVAyPZ53folnQZMBraUD5QBYJOkGVSjjxM7Lh8AvulHfdEf/5R7F88Br1ENCCX3EWx/mUuaD1wKnGt76MMkmY9g/+F13imZN1eyba/vJI23vafc6j1Yd0HRW5JGUw0GLbP9culO7i1g+wdJ71KtHzVO0sFlxkje45vlbGCOpIuBscARVDOGknmLDOstY7Y/tH2c7Um2J1F9kTzT9rfASuC6suvUTODHoSmpMfJJmtLRnAPsKMfJvaEkzQZuB+bY/rXj1ErgakljJE2mWlB8Yx01xrBJ5s31HjCl7EhyCNXi4StrrimGx0pgfjmeD/zTDMEYgco6Ik8B220/2HEquTeUpGOHdoSVdChwHtXaUWuBK8tlybxBbC+2PVB+l18NvGN7Hsm8VfoyQ+h/eh24mGqx0V+B6+stJ3rsPkknUd2f+gWwsPQn9+Z6FBgDrC4zAtfbXmh7q6QVwDaqW8luKlOUY4STdDnwCHAs8JqkzbYvTObNZXuvpJuBN4FRwNO2t9ZcVvSYpOeBWcAxkr6imuF7H7BC0gKqXWOvqq/C6IOzgWuBD8uaMlAt+5Dcm2s8sLTsHnkQsML2KknbgOWS7gE+oBoojGa7nWTeGtp3F0dERERERERERLRBXdvOR0RERERERERETTIgFBERERERERHRMhkQioiIiIiIiIhomQwIRURERERERES0TAaEIiIiIiIiIiJaJgNCEREREREREREtkwGhiIiIiIiIiIiWyYBQRERERERERETL/AV90B/2dV2rjwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,10))\n",
    "sns.kdeplot((imb_bars.log_ret - imb_bars.log_ret.mean()) / imb_bars.log_ret.std(), label=\"Imbalance bars\")\n",
    "sns.kdeplot((dollar_bars.log_ret - dollar_bars.log_ret.mean()) / dollar_bars.log_ret.std(), label=\"Dollar bars\")\n",
    "sns.kdeplot(np.random.normal(size=len(imb_bars)), label=\"Normal\", color='black', linestyle=\"--\")\n",
    "plt.title()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_acf(dollar_bars.log_ret, lags=10, zero=False)\n",
    "plt.title('Dollar Bars AutoCorrelation')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_acf(imb_bars.log_ret, lags=10, zero=False)\n",
    "plt.title('Dollar Imbalance Bars (num_ticks_init = 100k, num_prev_bars=3) AutoCorrelation')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "imb_bars['date_time'] = pd.to_datetime(imb_bars.date_time)\n",
    "dollar_bars['date_time'] = pd.to_datetime(dollar_bars.date_time)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion\n",
    "\n",
    "As we can see imbalance bars distribution is far from normal, they are more autocorrelated comparing to dollar bars, however, the key goal of imbalance/run bars is equal amount of information inside of each bar. That is why we should consider using information theory to research properties of imbalance bars in comparison with time/dollar bars."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
